盲目搜索的英文
blind search
brute force search
例句与用法
- ( 2 ) bayesian network methods can avoid subjective prejudice brought by apriority information , sightless search when we lack sample information , and the infection of interferential factors
( 2 ) bayesian网络中的理论方法既可避免只使用先验信息可能带来的主观偏见，和缺乏样本信息时的大量盲目搜索，也可避免只使用后验信息带来的干扰因素的影响。 - In order to avoid blind searching ergodicity in the overall situation before reducing the searching space of the variable optimized in chaos optimization algorithm , an optimization algorithm based on the chaos searching direction
摘要为了克服混沌优化方法在缩小优化变量的搜索空间前所进行的全局性、遍历性的盲目搜索，提出了一种基于混沌搜索方向的全局最优方法。 - Comparing with non - bnyain methods , it ' s prominent featares lay in that it combines the prior and posterior information , which avoids the disadvantag of subjective bias caused by simply using the prior information only , of blind search caused by the incomplete sample information , of noise affection caused by simply using the sample information only if we choice a suitable priof , we can conduct the bayesian leaming effectively , so it fits the problems of data mining and machine leaming that possess charaters of probability and statistics , especially when the samples are rare
与非贝叶扬方法相比，贝叶斯方法的特出特点是其学习机制可以综合先验信息和后验信息，既可避免只使用先验信息可能带来的主观偏见，和缺乏样本信息时的大量盲目搜索与计算，也可避免只使用样本信息带来的噪音的影响只要合理地确定先验，就可以进行有效的学习。因此，适用于具有概率统计特征的数据采掘和机器学习（或发现）问题，尤其是样本难得的问题 - The self - tuning algorithm of the parameter adopts eigenvalue of the systemic error and derivative error and so on . thus this method can overcome the disadvantage of the previous method which make the calibrating date not match up to the moveable track of the system , and improve the adaptability , rapidity and robustness of the human simulating intelligent control ' s algorithm
该方法将误差、误差导数等特征量引入参数在线校正公式，克服了以往采用盲目搜索法时校正量与系统实际运行轨迹不匹配的缺点，提高了仿人智能算法的适应性，快速性和鲁棒性。 - In the optimization of multi - dimensions function , this method definite the searching direction through the chaos firstly , make the problem to a single - dimension optimization question , then solve the single - dimension optimization question with other searching algorithms , this method can correct this default
在多维函数优化当中，该方法首先通过混沌机制确定搜索方法，将问题转化为一维搜索问题，然后采用其他搜索算法求解一维优化问题，此方法有利于改善盲目搜索的缺点。
